Modernizing C++ Testing Automated Test Discovery And Framework Selection

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Introduction

In the realm of software development, testing is a cornerstone of ensuring code quality, reliability, and maintainability. Particularly in C++ projects, a robust testing strategy is paramount due to the language's complexity and potential for subtle errors. In this article, we delve into the crucial aspects of modernizing C++ testing, focusing on automated test discovery and the selection of appropriate frameworks. The discussion revolves around enhancing the testing process within the Icinga 2 project, addressing the limitations of the existing approach, and exploring alternative solutions.

Current Limitations of Icinga 2's Testing Approach

Currently, Icinga 2 employs an outdated method for integrating Boost Test units as CTest targets. This approach relies on an aged third-party CMake module, accompanied by custom fixes accumulated over time to accommodate newer CMake versions. This legacy system exhibits several significant limitations:

  1. Manual Test Enumeration: The module necessitates the manual enumeration of all tests, leading to a substantial amount of boilerplate code. This contrasts sharply with more modern approaches that offer automated test discovery, streamlining the process and reducing the burden on developers.
  2. Build Artifact Overload: The module's reliance on add_executable() forces the construction of optional tests as standalone binaries. This results in the generation of numerous 200+MB build artifacts, significantly inflating build times and storage requirements. Moreover, the practice of building the entire project sources for each test binary imposes an n-times linker cost on every build, further exacerbating the issue.
  3. Inflexibility: The current system lacks the flexibility to specify per-test properties, a feature that has become increasingly necessary to address specific testing requirements, such as certificate fixture dependencies.
  4. Confusing Test Case Prefixes: The module mandates the addition of meaningless and confusing prefixes to test cases, hindering readability and maintainability. For example, test cases might be prefixed with strings like "base_remote-foo/bar", which adds unnecessary clutter and obscures the actual test intent.

These limitations collectively impede the efficiency and effectiveness of the testing process, highlighting the need for a modernized approach.

Addressing the Limitations: Two Potential Paths Forward

To overcome the aforementioned limitations and modernize the C++ testing process, two primary paths forward emerge:

1. Developing a Custom CMake Module for Automated Test Discovery

One potential solution involves crafting a new CMake module specifically designed for automated test discovery after the build process. This module would leverage the output of the <test-binary> --list-content=HRF command to identify and register tests. While a starting point could be derived from existing projects like this, its unmaintained status and the unlikelihood of its inclusion in CMake or Boost necessitate a fresh implementation.

Advantages of a Custom Module:

  • Dependency Mapping: A custom module offers the distinct advantage of mapping dependencies from Boost.Test labels defined in the test unit source code to CTest properties. This capability is particularly valuable for scenarios like the certificate fixture dependencies required by specific tests, ensuring that tests are executed with the necessary prerequisites.
  • Tailored Functionality: Building a custom module allows for precise tailoring of functionality to the specific needs of the project. This ensures that the testing process aligns seamlessly with the project's requirements and workflows.

Challenges of a Custom Module:

  • Development Effort: Creating and maintaining a custom CMake module requires significant development effort, including design, implementation, testing, and ongoing maintenance.
  • Potential for Duplication: If similar functionality is eventually incorporated into CMake or Boost, the custom module may become redundant, leading to duplicated effort.

2. Migrating to a Unit Test Framework with Built-in Automation Support

An alternative approach entails transitioning to a unit test framework that inherently supports automated test discovery. This strategy eliminates the need for a custom CMake module, leveraging the framework's built-in capabilities to streamline the testing process.

Advantages of Framework Migration:

  • Reduced Boilerplate: Modern frameworks often provide mechanisms for automated test discovery, significantly reducing the amount of boilerplate code required to define and register tests.
  • Enhanced Features: Many contemporary frameworks offer advanced features such as thread-safe asserts, which are absent in older frameworks like Boost.Test. These features enhance the robustness and reliability of tests.
  • Community Support: Popular frameworks benefit from extensive community support, providing a wealth of documentation, tutorials, and assistance for developers.

Framework Options:

  • GoogleTest: GoogleTest boasts built-in support within CMake, simplifying integration. Its header-only distribution minimizes dependencies, requiring only the inclusion of the header in the third-party/Gtest directory.
  • doctest: doctest stands out as a single-header framework renowned for its superior performance and richer feature set compared to GoogleTest. However, it necessitates the inclusion of its own CMake module.

Challenges of Framework Migration:

  • Migration Effort: Transitioning to a new framework involves a learning curve and the need to adapt existing tests to the new framework's syntax and conventions.
  • Potential Compatibility Issues: Compatibility issues may arise during the migration process, requiring careful attention and potential code modifications.

Building a Single Test Executable

Regardless of the chosen path—developing a custom module or migrating to a new framework—a common strategy involves building a single test executable using add_executable() and target_link_libraries(). This executable would encompass all currently enabled tests. Subsequently, a discovery function would be invoked to populate the test targets, ensuring that all tests are properly registered and executed.

This approach offers several benefits:

  • Reduced Build Artifacts: By consolidating tests into a single executable, the number of build artifacts is significantly reduced, alleviating storage and build time overhead.
  • Optimized Linking: Linking all tests into a single executable minimizes the linker cost associated with building multiple test binaries.
  • Simplified Management: Managing a single test executable simplifies the testing process, making it easier to run tests, analyze results, and identify issues.

Deep Dive into GoogleTest and doctest

When considering a transition to a new unit test framework, GoogleTest and doctest emerge as prominent contenders. Let's delve deeper into their features, advantages, and disadvantages:

GoogleTest

GoogleTest, developed by Google, is a widely adopted C++ testing framework known for its comprehensive feature set, robust assertions, and seamless integration with CMake. Its widespread use and extensive documentation make it a popular choice for many C++ projects.

Key Features of GoogleTest:

  • Rich Assertion Set: GoogleTest provides a rich set of assertions for verifying various conditions, including equality, inequality, boolean expressions, and exceptions.
  • Test Fixtures: Test fixtures allow developers to set up a common environment for multiple tests, reducing code duplication and improving maintainability.
  • Parameterized Tests: Parameterized tests enable the execution of the same test logic with different inputs, facilitating comprehensive testing.
  • Death Tests: Death tests verify that a program terminates as expected under specific conditions, such as when an assertion fails or an exception is thrown.
  • Value-Parameterized Tests: Value-parameterized tests combine the benefits of parameterized tests and test fixtures, allowing for the execution of tests with different inputs and within different environments.
  • Type-Parameterized Tests: Type-parameterized tests enable the testing of template code with different types, ensuring that the code functions correctly across a range of scenarios.
  • Automatic Test Discovery: GoogleTest integrates seamlessly with CMake's add_test command, enabling automatic test discovery and registration.

Advantages of GoogleTest:

  • Wide Adoption: Its widespread adoption translates to a large community, extensive documentation, and ample resources for developers.
  • CMake Integration: GoogleTest's built-in support within CMake simplifies integration and streamlines the testing process.
  • Comprehensive Feature Set: The framework's rich feature set caters to a wide range of testing needs, from basic unit tests to complex integration tests.

Disadvantages of GoogleTest:

  • Header-Only Distribution: While a header-only distribution simplifies deployment, it can potentially increase compile times due to the inclusion of headers in multiple compilation units.
  • Verbose Syntax: Some developers find GoogleTest's syntax to be verbose compared to other frameworks.

doctest

doctest is a lightweight, single-header C++ testing framework renowned for its speed, flexibility, and ease of use. It prioritizes simplicity and performance, making it an attractive option for projects where these factors are paramount.

Key Features of doctest:

  • Single-Header Distribution: doctest's single-header distribution simplifies integration and reduces dependencies.
  • Fast Compilation Times: The framework's design emphasizes fast compilation times, making it well-suited for large projects with frequent builds.
  • Minimalist Syntax: doctest's syntax is concise and intuitive, reducing boilerplate and improving readability.
  • Subcase Support: Subcases allow developers to structure tests into logical units, making it easier to organize and maintain tests.
  • Expression Assertions: Expression assertions provide detailed information about the evaluated expressions, aiding in debugging and understanding test failures.
  • Stringification: doctest automatically stringifies objects for output in assertions, simplifying the process of displaying complex data structures.

Advantages of doctest:

  • Speed and Performance: doctest's lightweight design and focus on performance result in fast compilation and execution times.
  • Ease of Use: Its minimalist syntax and single-header distribution make doctest easy to learn and integrate into projects.
  • Flexibility: doctest's subcase support and expression assertions enhance its flexibility and allow for more expressive tests.

Disadvantages of doctest:

  • Smaller Community: Compared to GoogleTest, doctest has a smaller community, which may translate to fewer available resources and support.
  • Separate CMake Module: doctest requires the inclusion of its own CMake module, which can add complexity to the build process.

Conclusion

Modernizing C++ testing is crucial for ensuring the quality, reliability, and maintainability of software projects. The limitations of the current approach in Icinga 2 highlight the need for a more efficient and flexible testing strategy. Two primary paths forward emerge: developing a custom CMake module for automated test discovery or migrating to a unit test framework with built-in automation support.

Each approach presents its own set of advantages and challenges. Crafting a custom module offers tailored functionality and dependency mapping capabilities, but requires significant development effort. Migrating to a framework like GoogleTest or doctest provides access to advanced features and community support, but necessitates a learning curve and potential compatibility adjustments.

The decision of which path to pursue hinges on the specific needs and priorities of the project. Factors to consider include the availability of development resources, the desired level of customization, and the importance of features like thread-safe asserts and expression assertions.

Regardless of the chosen path, building a single test executable and leveraging automated test discovery are essential steps in modernizing the C++ testing process. These strategies streamline the testing workflow, reduce build times, and enhance the overall efficiency of the software development lifecycle.